Radicalbit offers a complete, integrated and fully supported pure Fast Data solution

Radicabit Distribution (RBD) is a collection of open source (Apache 2) software products connecting, leveraging and exploiting data, network, intelligence and computing power.
RBD1, Radicalbit open source distribution, includes modern, present and future-proof technologies, fully integrated, forming an end-to-end data pipeline computing environment in which a pool of software, leveraging computers collaborating over the network, take part to solve complex problems in order to achieve a common goal.

SOLUTIONS

ULTIMATE TOOLS FOR YOUR BUSINESS

Getting big data right is not an easy task. It requires knowledge, expertise, culture, time and the right tool for the right job.

Years of experience in studying and working on big data technologies have helped us to understand the technology, its pros & cons, the do and the don’ts and develop a strong vision about the future of Big Data.
We selected a list of open source technologies and we glued them together in order to develop and support a modern and future-proof fast data distribution, RBD1.
RBD1 architectural blueprint:


* Integration & Support
** Integration Only
* Future Enhancement

ANY SUFFICIENT ADVANCED TECHNOLOGY IS INDISTINGUISHABLE FROM MAGIC

THE ARCHITETURAL BLUEPRINT

Timely and relevant information can fuel significant insights. From consumer or competitor patterns and behavior, anomaly detection, supply chain optimization and more. Developing a data ingestion strategy is therefore of quite importance.

Data Ingestion is the process of loading a small or large amount of data, mainly for analytical needs, from a variety of sources coming in different formats and at different speed.
Factors like the information explosion and the rise of the Internet of Things in the information age are creating new business opportunities. However, in order to exploit opportunities, organizations are facing new technological challenges. Traditional tools may not be adequate to address demands for scalability, performance, fault tolerance, real time, etc.

MONEY NEVER SLEEPS

UNIFIED CONTINUOUS INGESTION

Hadoop and the concept of the Enterprise Data Lake have generated tremendous expectations. A Data Lake is a large-scalable repository that holds a large amount of raw data in its native format. A Data Lake is not a Data Warehouse nor it is a replacement for it.

Data Lake and Data Warehouse are both optimized for different purpose. Organizations should use a Data Lake for Analytics Purposes, not for collaboration between operational systems. Citing Martin Fowler “The lake is too complex to trawl for operational communication. It may be that analysis of the lake can lead to new operational communication routes, but these should be built directly rather than through the lake”.

THE REASON OF THINGS IS IN THEIR EXISTENCE

HUB & SPOKE ARCHITECTURE

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